Every company deserves its second brain

No. Your team keeps its CRM, email, chat, documents and project tools. The second brain adds written company knowledge and connects those tools through each person's own logins. Instead of explaining the business to a blank chat window every time, people can ask with that context already in place.

We switched on Pirxey World, our second brain, on 15 May 2026 and publish how it's going. By October six people had made 235 changes to the shared core, and the founder was third on that list. Not everything went well: in September, 26% of the 77 people who answered our survey hadn't heard of Pirxey World at all. You get both lessons.

No. Our own survey counts both columns: 912 hours given back and 156 lost in two weeks, across 77 people, by their own estimate. That's a self-report, not a measurement. For your workflow we take a baseline before the start, so reported time and measured change stay separate.

No. People learn on the real workflow, on their own accounts. What moved people at Pirxey was someone sitting next to them for an hour, a walkthrough and a first-steps page with seven things to try.

No. Ours runs mostly on Claude, and 70% of the people who answered our own survey use models from two or more families. The pattern works with any of them: written knowledge, an index the assistant reads first, recipes, and tools connected with each person's own logins. We set it up on what you already pay for. No migration, no new system to learn.

Yes. The knowledge is plain files in a repository you own. The model can be a hosted one in your own cloud account (AWS Bedrock, Azure OpenAI or Google Vertex AI), or an open model such as Llama or Mistral on your own servers, served with Ollama or vLLM. Open models on your hardware keep the text in-house, but you pay for the hardware and smaller models need more checking. We can run the first workflow on both before you decide.

The assistant works through each person's own logins, so it sees exactly what that person already sees. Removing someone's access in a tool removes it for their assistant too. Written knowledge gets separate homes: company-wide, per department, a strategic one with fewer readers and a private one per person. Only the question and the text the assistant picks go to the model provider. An answer can still reach someone who couldn't read its sources, so shared knowledge is checked before it's saved. Who should see what was a problem long before AI, and an assistant inherits it, so we review access with you before connecting anything.

Readiness work identifies gaps and priorities for a decision: twelve questions across six pillars, a band and the first moves. An adoption program puts the first move into use with your people and measures what happens.

We quote after the first conversation, once we know your tools and the first workflow. You get the price before we start.

The agreed knowledge structure, workflow configuration, access rules, training material and measurement record stay with your team. You can use the pilot results to decide whether to extend, change direction or stop. New tools and more departments are separate decisions.

We bring engineers with AI, integration, data and security experience. You bring the business context, the people who own the workflow and someone to lead adoption internally. Together we turn that knowledge into skills and jobs your team can maintain.

Start with a conversation about your tools and a workflow your team repeats. We identify the knowledge and access it needs, agree what success would look like and propose the first version before implementation begins.